Background: The major bottleneck in genome sequencing is no longer data generation, but the computational challenges around data analysis, display and integration. New approaches and methods are, therefore, required to meet these challenges. Visual analytics is the representation and presentation of data that exploits human visual perception abilities in order to amplify cognition. Opportunities exist for African researchers to expand the use of visual discovery tools and curated datasets to enable visual discovery (exploration, mining and analysis via interactive visual interfaces) of bioinformatics results from high-quality genomics research.
Methods: We are developing a system of visual analytics resources that are based on molecular and clinical data including molecular consequences of single nucleotide variants; the RNA-seq expression levels of transcripts; and the functional sites in protein sequences.
Results: We have developed an initial set of visual analytics resources with the use case as the major intrinsic protein family of water and glycerol transporters. Members of these protein family have been implicated in diverse cardiometabolic diseases. The computational resources developed can be adapted for gene lists including those obtained from high-throughput assays. The long-term goal of the project is to empower researchers to make discoveries from largescale molecular and clinical datasets to support decision-making on genetic and environmental determinants of cardiometabolic diseases in Africa.